Evidence map›Paper›PMID 42383628›Full record

ArticleJournal of diabetes science and technology2026

Continuous Glucose Monitoring Metrics for Predicting Adverse Neonatal Outcomes in Individuals Undergoing Gestational Diabetes Screening.

Caleb Griffiths, Rafael Bravo Santos, Sarah A Wernimont, Julie Anderson, Megan Kristan, Erika S Helgeson, Lisa S Chow, Michal Fishel Bartal

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In one paragraph

Article in Journal of diabetes science and technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Caleb GriffithsDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, USA.ORCID 0009-0007-3403-5673
Rafael Bravo SantosDepartment of Obstetrics, Gynecology, and Reproductive Sciences, McGovern Medical School at The University of Texas Health Science Center at Houston, USA.
Sarah A WernimontDivision of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology and Women's Health, Medical School, University of Minnesota, Minneapolis, USA.
Julie AndersonDivision of Diabetes, Endocrinology and Metabolism, Department of Medicine, Medical School, University of Minnesota, Minneapolis, USA.
Megan KristanDivision of Diabetes, Endocrinology and Metabolism, Department of Medicine, Medical School, University of Minnesota, Minneapolis, USA.
Erika S HelgesonDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, USA.
Lisa S ChowDivision of Diabetes, Endocrinology and Metabolism, Department of Medicine, Medical School, University of Minnesota, Minneapolis, USA.ORCID 0000-0002-6210-2307
Michal Fishel BartalDivision of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, USA.

Funding

Prolonged Daily Fasting As a Viable Alternative to Caloric Restriction in At-Risk Obese HumansR01DK124484 · NIDDK · UNIVERSITY OF MINNESOTA · PI CHOW, LISA SENYE · 2020 to 2023
$2.7M
Time Restricted Eating As a Viable Alternative to Caloric Restriction for Treating Hyperglycemia in a Population with Type 2 (T2DM) diabetesR01DK129668 · NIDDK · UNIVERSITY OF MINNESOTA · PI CHOW, LISA SENYE · 2022 to 2024
$949k
NIDDK NIH HHS R01 DK124484NIDDK NIH HHS R01 DK129668
6 · The paper itself

Abstract

objectivesThis study evaluates whether continuous glucose monitoring (CGM) metrics predict adverse neonatal outcomes among individuals undergoing gestational diabetes screening. Building on findings by Fishel Bartal et al, who reported an association between ≥10% time above 140 mg/dL and a composite neonatal outcome, this analysis examines 13 additional CGM-derived measures reflecting glycemic variability (GV) and glycemic extremes.

methodsEighty-four pregnant individuals wore CGM devices for 10 days following a 1-hour 50 g glucose challenge test. Generalized estimating equation logistic regression models assessed associations between CGM metrics and a composite neonatal outcome consisting of large-for-gestational-age birth, need for intravenous glucose treatment, or shoulder dystocia. Model discrimination was quantified using the area under the receiver operating characteristic curve (AUROC).

resultsSeveral CGM measures-including mean glucose, standard deviation (SD), maximum glucose, %Time >140 mg/dL, %Time >120 mg/dL, glucose management indicator (GMI), mean of daily differences (MODD), mean amplitude of glycemic excursions (MAGE), area under the CGM curve (AUC-CGM), and high blood glucose index (HBGI)-were significantly associated with adverse neonatal outcomes (

conclusionsContinuous glucose monitoring metrics reflecting sustained or high-level hyperglycemia, rather than GV-focused metrics, more strongly predicted adverse neonatal outcomes. These findings suggest that persistent or extreme maternal glucose elevations, rather than variability alone, may drive neonatal risk and support refining CGM-based screening approaches in pregnancy.

Indexed as

continuous glucose monitoringgestational diabetes screeningglycemic variabilityhyperglycemialarge for gestational ageneonatal

Identifiers

PMID42383628
PMCPMC13323036

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.